The broad long-term objectives of the proposed research are evaluation of the role of age trajectories of physiological indices as well as other factors as determinants of exceptional health among the elderly, by combining data collected in different longitudinal studies. Specific aims: 1. Evaluate effects of age trajectories of each of the selected physiological indices, as well as other factors measured in Framingham Heart Study (FHS), Framingham Offspring Study (FHSO) and Honolulu Heart Study (HHS), on exceptional health among the elderly using traditional statistical methods. Evaluate changes in the effects of risk factors with age. 2. Develop mathematical and computer models describing mechanisms generating age dynamics of each physiological index including possibility of their homeostatic regulation and dynamic connection to health outcomes. Use these models in the analysis of FHS, HHS and FHSO data to: a) evaluate age related changes in coefficients of homeostatic regulation with age in each of selected physiological indices and their role in healthy aging;b) evaluate changes in the role of each index in determining health outcomes with age. 3. Evaluate age-related changes in characteristics determining joint dynamics of a set of selected physiological indices, as well as changes in effects of these indices on health outcomes. Evaluate age trajectories of "normal" or "optimal" physiological state as well as the range of tolerable deviations from it. For this purpose develop mathematical and computer model describing joint age dynamics of a set of physiological indices and its connection to health outcomes. Use this model in the analysis of FHS, FHSO and HHS data to address issues formulated above. 4. Evaluate dynamic determinants of exceptional health at late ages in the joint analysis of FHS, FHSO and HHS data. For this purpose develop compatible mathematical and computer models describing joint dynamics of a set of selected physiological indices and their connection to health outcomes for each of three selected data sets and use these models in joint analysis of these three longitudinal data sets. Evaluate differences and similarities in dynamic determinants of exceptional health at late ages in populations participating in joint analysis of data. Evaluate contribution of genetic and non-genetic factors in exceptional health at late ages in the joint analysis of FHS and FHSO data.